构建新闻中法律案件的情感、道德与事件数据集，助力分析媒体偏见。
E2MoCase: A Dataset for Emotional, Event and Moral Observations in News Articles on High-impact Legal Cases
- 基于NLP模型提取新闻中的情感、道德和事件信息。
- 覆盖高影响力法律案件，支持多维度叙事分析。
- 适合研究媒体偏见、司法传播与公众认知的学者使用。
媒体报道法律案件的方式会显著影响公众舆论，常隐含微妙偏见，进而塑造社会对正义与道德的看法。分析这些偏见需综合考察叙述中的情感基调、道德框架及具体事件。本文提出E2MoCase，一个新型数据集，旨在促进对法律叙事与媒体报道中情感、道德价值和事件的集成分析。通过利用先进的情绪识别、道德价值判断与事件抽取模型，E2MoCase为法律案件的媒体呈现提供多维度视角。该数据集涵盖高影响力法律案件，支持跨案例比较与深度分析。
原文摘要 · Abstract (English)
The way media reports on legal cases can significantly shape public opinion, often embedding subtle biases that influence societal views on justice and morality. Analyzing these biases requires a holistic approach that captures the emotional tone, moral framing, and specific events within the narratives. In this work we introduce E2MoCase, a novel dataset designed to facilitate the integrated analysis of emotions, moral values, and events within legal narratives and media coverage. By leveraging advanced models for emotion detection, moral value identification, and event extraction, E2MoCase offers a multi-dimensional perspective on how legal cases are portrayed in news articles.
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